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• W2108335893 abstract "Stored water, i.e., soil moisture in the root zone, is the most important factor governing energy and moisturefluxes at the land atmosphere interface. Knowledge of stored water is critical for accurate modeling of crop developmentand yield. Even though crop model simulations have become increasingly realistic, their estimates of crop growth divergefrom reality over time. A promising way to improve model estimates is to incorporate independent observations in themodel, e.g. remotely sensed data that are sensitive to soil moisture, such as microwave observations at low frequencies.Integrated crop growth-microwave models can utilize satellite observations to improve model estimates ofevapotranspiration, biomass, and yield. This research aims to calibrate a crop growth model for a growing season of cornin North-Central Florida. This calibrated model will be linked to a microwave brightness model toestimate brightness signatures of a dynamic canopy.<br><br>The CERES-Maize model was implemented for weather and soil conditions in North-Central Florida andcalibrated using data from our second Microwave Water and Energy Balance Experiment (MicroWEX-2). MicroWEX-2was an extensive field experiment conducted by the Center for Remote Sensing to monitor a growing season of corn fromDay of Year (DoY) 78 to DoY 154 in 2004. During MicroWEX-2, we observed micrometeorological, soil, and vegetativeconditions along with microwave signatures for a nine-acre field. The model was ported from MS Windows to the LinuxOS and calibrated using a combination of grid search and simulated annealing methods. The six cultivar coefficients (P1,P2, P5, G1, G3, and PHINT) were modified to minimize the normalized sum of square errors (SSE) of biomass and LAI,the two most important canopy parameters for the microwave brightness model.<br><br>Overall the model estimated realistic total biomass with a root mean square error (RMSE) of 0.880 Mg/ha.However, the partitioning of total biomass into stem and leaf biomasses were under and overestimated, respectively. LAImatched well with the observations with a RMSE of 0.105. The model estimated realistic daily latent heat flux with anRMSE of 42.07 W/m2 This error is similar in magnitude to the experimental errors using Eddy covariance systems. Thesoil moisture and temperature profiles of deeper soil layers matched reasonably well with observations, with RMSE of 1-3.5% and 1.4-3.7 K, respectively. Near surface soil moisture and temperature (0-5 cm) were less realistic because thehydrological processes near the surface need to be modeled on a much shorter timestep than is allowed by the crop model." @default.
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• W2108335893 date "2005-01-01" @default.
• W2108335893 modified "2023-09-26" @default.
• W2108335893 title "Calibration of the CERES-Maize Model for Linkage with a Microwave Remote Sensing Model" @default.
• W2108335893 doi "https://doi.org/10.13031/2013.20036" @default.
• W2108335893 hasPublicationYear "2005" @default.
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